Impact of Magnetic Field Configuration on Heat Transport in Stellarators and Heliotrons.

We assess the magnetic field configuration in modern fusion devices by comparing experiments with the same heating power, between a stellarator and a heliotron. The key role of turbulence is evident in the optimized stellarator, while neoclassical processes largely determine the transport in the heliotron device. Gyrokinetic simulations elucidate the underlying mechanisms promoting stronger ion scale turbulence in the stellarator. Similar plasma performances in these experiments suggests that neoclassical and turbulent transport should both be optimized in next step reactor designs.

Turbulence Mechanisms of Enhanced Performance Stellarator Plasmas.

We theoretically assess two mechanisms thought to be responsible for the enhanced performance observed in plasma discharges of the Wendelstein 7-X stellarator experiment fueled by pellet injection. The effects of the ambipolar radial electric field and the electron density peaking on the turbulent ion heat transport are separately evaluated using large-scale gyrokinetic simulations. The essential role of the stellarator magnetic geometry is demonstrated, by comparison with a tokamak.

Stellarators Resist Turbulent Transport on the Electron Larmor Scale.

Electron temperature gradient (ETG)-driven turbulence, despite its ultrafine scale, is thought to drive significant thermal losses in magnetic fusion devices-but what role does it play in stellarators? The first numerical simulations of ETG turbulence for the Wendelstein 7-X stellarator, together with power balance analysis from its initial experimental operation phase, suggest that the associated transport should be negligible compared to other channels. The effect, we argue, originates essentially from the geometric constraint of multiple field periods, a generic feature of stellarators.

Erratum: Distinct Turbulence Saturation Regimes in Stellarators [Phys. Rev. Lett. 118, 105002 (2017)].

This corrects the article DOI: 10.1103/PhysRevLett.118.105002.

Distinct Turbulence Saturation Regimes in Stellarators.

In the complex 3D magnetic fields of stellarators, ion-temperature-gradient turbulence is shown to have two distinct saturation regimes, as revealed by petascale numerical simulations and explained by a simple turbulence theory. The first regime is marked by strong zonal flows and matches previous observations in tokamaks. The newly observed second regime, in contrast, exhibits small-scale quasi-two-dimensional turbulence, negligible zonal flows, and, surprisingly, a weaker heat flux scaling. Our findings suggest that key details of the magnetic geometry control turbulence in stellarators.

Controlling turbulence in present and future stellarators.

Turbulence is widely expected to limit the confinement and, thus, the overall performance of modern neoclassically optimized stellarators. We employ novel petaflop-scale gyrokinetic simulations to predict the distribution of turbulence fluctuations and the related transport scaling on entire stellarator magnetic surfaces and reveal striking differences to tokamaks. Using a stochastic global-search optimization method, we derive the first turbulence-optimized stellarator configuration stemming from an existing quasiomnigenous design.

Zonal flow dynamics and control of turbulent transport in stellarators.

The relation between magnetic geometry and the level of ion-temperature-gradient (ITG) driven turbulence in stellarators is explored through gyrokinetic theory and direct linear and nonlinear simulations. It is found that the ITG radial heat flux is sensitive to details of the magnetic configuration that can be understood in terms of the linear behavior of zonal flows. The results throw light on the question of how the optimization of neoclassical confinement is related to the reduction of turbulence.

Optimizing stellarators for turbulent transport.

Up to now, the term "transport-optimized" stellarators has meant optimized to minimize neoclassical transport, while the task of also mitigating turbulent transport, usually the dominant transport channel in such designs, has not been addressed, due to the complexity of plasma turbulence in stellarators. Here, we demonstrate that stellarators can also be designed to mitigate their turbulent transport, by making use of two powerful numerical tools not available until recently, namely, gyrokinetic codes valid for 3D nonlinear simulations and stellarator optimization codes. Two initial proof-of-principle configurations are obtained, reducing the level of ion temperature gradient turbulent transport from the National Compact Stellarator Experiment baseline design by a factor of 2-2.5.

An ambulatory persistence power curve: motor planning affects ambulatory persistence in Parkinson's disease.

BACKGROUND/OBJECTIVES: When performing activity associated with walking, the amount of walking a person does often will depend on their plans. This study was designed to evaluate the relationship between motor planning and ambulatory persistence in participants with Parkinson's disease (PD) and to see if ambulatory persistence was related to the ability to perform activities of daily living (ADL). METHODS: 20 individuals with idiopathic PD were recruited to perform the Trail making Test (a test of motor planning) and to wear a step activity monitor for 48h. The measurement of persistence of an ambulatory event consisted of the number of steps taken during an event and an ambulatory event was defined as continuous ambulation (taking step) without pausing for 3 or more seconds. The resumption of taking step (ambulation) after 3 or more seconds counted as a new ambulatory event. UPDRS-motor and ADL scale were also obtained. ANALYSIS AND RESULTS: The cumulative percentage of the total ambulatory events at each number of steps was plotted for each subject which when plotted could be described as a sigmoid curve. We found that this sigmoidal curve defined by the equation y=x(n)/(k(n)+x(n)), fit the data well, where k represents a constant specific to each subject, x represents the number of steps during each ambulatory event, and y represents the projected percentage of movement events containing x number of steps or less. (Root Mean Square Error (RMSE)=0.02, R(2)=0.98). Trail making test part A was highly associated with the constant k (R=-0.74, p<0.001). The constant k was also highly associated with the UPDRS ADL subscale (R=-0.81, p=0.0001). A forward bivariate regression model including Part A of the Trail making test, and the UPDRS-ADL subscale predicted 66% of the variability of the constant k. The overall number of steps taken per day, and the UPDRS motor subscale did not contribute to the model. CONCLUSIONS: Defective motor planning in Parkinson's disease as measured by poor performance on a Trail making test is associated with a measurable alteration in ambulatory persistence, and altered ambulatory persistence, quantified by our proposed model parameter, correlates highly with the UPDRS ADL score. Thus, cognitive-motor planning defects might be a major source of disability in PD. We suggest that in future clinical practice gait tests can be used in order to quantify short-term planning ability in neurodegenerative diseases.

Time-frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?

The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies and can be quantified with a number of techniques. In this paper, real and simulated sleep spindles were regarded as AM/FM signals modeled by six parameters that define the instantaneous envelope (IE) and instantaneous frequency (IF) waveforms for a sleep spindle. These parameters were estimated using four different methods, namely the Hilbert transform (HT), complex demodulation (CD), matching pursuit (MP) and wavelet transform (WT). The average error in estimating these parameters was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT. The signal distortion induced by the use of a given method was greatest in the case of HT and MP. These two techniques would necessitate the removal of about 0.4s from the spindle data, which is an important limitation for the case of spindles with duration less than 1s. Although the CD method may lead to a higher error than HT and MP, it requires a removal of only about 0.23s of data. An application of this sleep spindle parameterization via the CD method is proposed, in search of efficient EEG-based biomarkers in dementia. Preliminary results indicate that the proposed parameterization may be promising, since it can quantify specific differences in IE and IF characteristics between sleep spindles from dementia subjects and those from aged controls.

Nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence for the optimized Wendelstein 7-X stellarator.

Ion-temperature-gradient turbulence constitutes a possibly dominant transport mechanism for optimized stellarators, in view of the effective suppression of neoclassical losses characterizing these devices. Nonlinear gyrokinetic simulation results for the Wendelstein 7-X stellarator [G. Grieger, in (IAEA, Vienna, 1991) Vol. 3, p. 525]-assuming an adiabatic electron response-are presented. Several fundamental features are discussed, including the role of zonal flows for turbulence saturation, the resulting flux-gradient relationship, and the coexistence of ion-temperature-gradient modes with trapped ion modes in the saturated state.

Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles.

The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies. In this work, the sleep spindle is modeled as an AM-FM signal and parameterized in terms of six parameters, three quantifying the instantaneous envelope (IE) and three quantifying the instantaneous frequency (IF) of the spindle model. The IE and IF waveforms of sleep spindles from patients with dementia and normal controls were estimated using the time-frequency technique of Complex Demodulation (CD). Sinusoidal curve-fitting using a matching pursuit (MP) approach was applied to the IE and IF waveforms for the estimation of the six model parameters. Specific differences were found in sleep spindle instantaneous frequency dynamics between spindles from dementia subjects and spindles from controls.

Modeling the time-varying microstructure of simulated sleep EEG spindles using time-frequency analysis methods.

The time-varying microstructure of sleep spindles may have clinical significance and can be quantified and modeled with a number of techniques. In this paper, sleep spindles were regarded as AM-FM signals modeled by six parameters. The instantaneous envelope (IE) and instantaneous frequency (IF) waveforms were estimated using four different methods, namely Hilbert Transform (HT), Complex Demodulation (CD), Wavelet Transform (WT) and Matching Pursuit (MP). The six model parameters were subsequently estimated from the IE and IF waveforms. The average error, taking into account the error for each model parameter, was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT, for three different spindle model examples. The amount of distortion induced by the use of a given method is also important; distortion was the greatest (0.4 sec) in the case of HT. Therefore, in the case of real spindles, one could utilize CD and MP and, if the spindle duration is more than 1 sec, HT as well.